GitLab

* refactor: change default block_size when not initialize

* reformat: add the min of block size

* docs: add space to docs

* docs: remove reduntant space

* pytorch examples

* pytorch mim no trainer

* cookiecutter

* flax examples

* missed line in pytorch run_glue

* tensorflow examples

* tensorflow run_clip

* tensorflow run_mlm

* tensorflow run_ner

* tensorflow run_clm

* pytorch example from_configs

* pytorch no trainer examples

* Revert "tensorflow run_clip"

This reverts commit 261f86ac1f1c9e05dd3fd0291e1a1f8e573781d5.

* fix: duplicated argument

* fix

* fix

* fix

* fix

* fix

* fix

* fix

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* pytorch examples

* tensorflow examples

* flax examples

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix .push_to_hub and cleanup get_full_repo_name usage

* Do not rely on Python bool conversion magic

* request changes

* initial replacements of asserts with errors/exceptions

* replace assert with exception in generation, align and bart

* reset formatting change

* reset another formatting issue

* Apply suggestion
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* don't touch this file

* change to 'is not False'

* fix type

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Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies

* Adapt repository creation to latest hf_hub

* Update all examples

* Fix other tests, add Flax examples

* Address review comments

* Fix typo

* Update README.md

* Update run_mlm_flax_stream.py

* Update README.md

* Compute true loss

* fixup

* final

* final

* final

* Update examples/flax/language-modeling/run_bart_dlm_flax.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* jax.tree_map => jax.tree_util.tree_map

* Compute true loss

* final

* fixup

* final

* final

* Update examples/flax/language-modeling/run_bart_dlm_flax.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* jax.tree_map => jax.tree_util.tree_map
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* [JAX] Replace all jax.tree_* calls with jax.tree_util.tree_*

* fix double tree_util

* [Flax] Add remat (gradient checkpointing)

* fix variable naming in test

* flip: checkpoint using a method

* fix naming

* fix class naming

* apply PVP's suggestions from code review

* add gradient_checkpointing to examples

* Add gradient_checkpointing to run_mlm_flax

* Add remat to longt5

* Add gradient checkpointing test longt5

* Fix args errors

* Fix remaining tests

* Make fixup & quality fixes

* replace kwargs

* remove unecessary kwargs

* Make fixup changes

* revert long_t5_flax changes

* Remove return_dict and copy to LongT5

* Remove test_gradient_checkpointing
Co-authored-by: sanchit-gandhi <sanchit@huggingface.co>

* zero chance anyone's using that constant no?

* `transformers-cli login` => `huggingface-cli login`

* `transformers-cli repo create` => `huggingface-cli repo create`

* `make style`

* add bart pretraining flax script

* fixup

* add bart pretraining flax script

* add BART to README

* add BART to README

* add BART to README

* add BART to README

* add BART to README

* add bos eos document

* Update README.md

* Update README.md

* Update examples/flax/language-modeling/run_bart_dlm_flax.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* final

* final

* final

* remove use_auth_token ing from_config
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* [Flax] Fix incomplete batches in example scripts

* fix dataloader batching

* convert jnp batch idxs to np array

* add missing `pad_shard_unpad` to final prediction generate step

* only `pad_shard_unpad` at inference time

* merge conflicts

* remove incomplete batch step from eval

* fix run_qa.py

* add `pad_shard_unpad` to run_flax_ner.py

* add `pad_shard_unpad` to run_flax_glue.py

* add `pad_shard_unpad` to run_image_classification.py

* make style

* fix mlm flax eval batches

* remove redundant imports

* generalize decay_mask_fn to find all layernorm params

* fixup

* generalising decay_mask_fn

* remove use_auth_token from from_config

* restore use_auth_token from_pretrained run_t5_mlm_flax

* Fix RESOURCE_EXHAUSTED error for large datasets on Flax example scripts

* using np.permutation for creating batch_idx

* train_samples_idx -> training_samples_idx

* fix type hints

* Add examples telemetry

* Alternative approach

* Add to all other examples

* Add to templates as well

* Put framework separately

* Same for TensorFlow

* Black preview

* Fixup too!

* Fix check copies

* Use the same version as the CI

* Bump black

* Fix t5 shard on TPU Pods

The current script doesn't work properly on a TPU pod because the global batch is not divided correctly per host.
This pull request fixes this issue by dividing the global batch to each host before it is shared on each host.

* fix style
Co-authored-by: ahmed-elnaggar <ahmed.elnaggar@allianz.com>

* fix formatting and remove use_auth

* Add use_auth_token to Flax examples

* [examples] max samples can't be bigger than then len of dataset

* do tf and flax

Fix typo in comment: proprocessed -> preprocessed

* Split file_utils in several submodules

* Fixes

* Add back more objects

* More fixes

* Who exactly decided to import that from there?

* Second suggestion to code with code review

* Revert wront move

* Fix imports

* Adapt all imports

* Adapt all imports everywhere

* Revert this import, will fix in a separate commit

* Updates the default branch from master to main

* Links from `master` to `main`

* Typo

* Update examples/flax/README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Speedup training by using numpy instead of jnp for batch shuffling
Co-authored-by: Yeb Havinga <y.t.havinga@mgrid.net>

fix typo

* use jax and jnp instead of numpy in data_loader

* return batches as np.ndarray

* use custom training arguments

* update tests

* Replace outdated model tags with their now-canonical pipeline types

* spam the CI till it's green